In data centers with raised floor architectures, vent tiles are typically distributed over the raised floor and locally distribute airflow from a plenum formed below the raised floor. The plenum is pressurized with cold air by blowers in one or more computer room air conditioning (CRAC) units. The vent tiles allow cold air to escape from the plenum and to travel from the raised floor to the intakes of rack-mounted equipment. The most common vent tile has a fixed 25% opening, however, vent tiles with larger fixed openings are available in standard sizes of 47%, 56% and 85%. In addition, it is common to install the vent tiles in front of each rack containing equipment. Consequently, the airflow provided to the equipment is relatively constant, as the tile configuration and blower speed are fixed and rarely changed.
However, the environment of a data center is dynamic because workload placement and power dissipation fluctuate considerably over time and space. To compensate for these fluctuations, zonal controllers are typically employed to control the CRAC set points and/or blower speeds in real time, and maintain the return air temperatures to the CRAC units below certain thresholds, or the highest intake temperatures of racks in thermal zones below their thresholds. Nevertheless, the zonal controllers are designed to respond to return air temperatures or the hot spots in thermal zones that can be affected by the CRAC units. As such, the temperature distribution inside the thermal zones is still non-uniform, which often results in overprovisioning of cooling capacity and is thus inefficient.
Another compensation technique is to manually adjust the vent tiles, for instance, by adding or moving the vent tiles based upon a prediction of where the vent tiles are needed to compensate for changing conditions in the data center environment. However, manual adjustment of the vent tiles is labor-intensive, error-prone and often non-intuitive. Thermal models are often developed to assist with the vent tile adjustments, but these models are typically time-consuming to generate and require skilled users to achieve accurate results.